This section is intended to provide a background or context to the invention that is recited in the claims. The description herein may include concepts that could be pursued, but are not necessarily ones that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, what is described in this section is not prior art to the description and claims in this application and is not admitted to be prior art by inclusion in this section.
Today, rules impact a huge number of target business applications ranging from insurance adjudication, loan approval, claims processing, credit scoring, product/service recommendations, order configuration and fraud detection. A typical application may implement between 100 and 1,000 rules. Complex rules are not only difficult to code into applications, they also difficult to maintain using traditional coding practices.
Semantic processing helps bridge the gap between human and computer syntax. Reducing the Human-Computer gap can ease conceptualization and enhance human activity with concept processing. Semantic processing may make use of ontologies which define objects (data), properties of those objections (e.g., relationships with other objects) and logic. This information may then be used to process the objects, for example, query, navigate, serialize, and reason.
There is interest in the extension of rules applications into Semantic Web Languages. The Semantic Web is based on the idea of incorporating a format descriptive form (e.g., XML with logical processing) and additional structures (e.g., inheritance, data types, axioms, etc.). This provides a duality between expressivity and some computational properties related to an ability to reason over data.
A complexity-read restriction for the expressivity of ontology web language (OWL) languages depends on a number of factors, for example:                1. Use of an open world assumption—meaning that information about facts which is not directly asserted is unknown (e.g., lack of a definition does not imply that the statement is false and/or there is no assumption that the known facts comprise all known facts); and        2. The possibility to have different people with the same name at the same time, people with the same aliases be same the person, etc.        
These factors make use of many ontology models questionable. One approach is to make ontological data more compact and to apply rules that make description by the ontology more compact and manageable.
Semantic Web Rule Language (SWRL) is a combination of the OWL DL and OWL Lite sublanguages with the Unary/Binary Datalog. It is an extension to OWL with Horn-style rules. SWRL provides expressivity and compatibility. Furthermore, it follows OWL's XML and RDF syntax. SWRL limits predicates to being OWL classes and properties.
What is needed is a way to evaluate/verify ontologies in order to determine their correctness/goodness.